NIPS Proceedings^β

Advances in Neural Information Processing Systems 9 (NIPS 1996)

The papers below appear in Advances in Neural Information Processing Systems 9 edited by M.C. Mozer and M.I. Jordan and T. Petsche.
They are proceedings from the conference, "Neural Information Processing Systems 1996."

• Text-Based Information Retrieval Using Exponentiated Gradient Descent Ron Papka, James P. Callan, Andrew G. Barto
• Why did TD-Gammon Work? Jordan B. Pollack, Alan D. Blair
• Neural Models for Part-Whole Hierarchies Maximilian Riesenhuber, Peter Dayan
• Temporal Low-Order Statistics of Natural Sounds Hagai Attias, Christoph E. Schreiner
• Reconstructing Stimulus Velocity from Neuronal Responses in Area MT Wyeth Bair, James R. Cavanaugh, J. Anthony Movshon
• 3D Object Recognition: A Model of View-Tuned Neurons Emanuela Bricolo, Tomaso Poggio, Nikos K. Logothetis
• A Hierarchical Model of Visual Rivalry Peter Dayan
• Neural Network Models of Chemotaxis in the Nematode Caenorhabditis Elegans Thomas C. Ferrée, Ben A. Marcotte, Shawn R. Lockery
• Extraction of Temporal Features in the Electrosensory System of Weakly Electric Fish Fabrizio Gabbiani, Walter Metzner, Ralf Wessel, Christof Koch
• A Neural Model of Visual Contour Integration Zhaoping Li
• Learning Exact Patterns of Quasi-synchronization among Spiking Neurons from Data on Multi-unit Recordings Laura Martignon, Kathryn B. Laskey, Gustavo Deco, Eilon Vaadia
• Complex-Cell Responses Derived from Center-Surround Inputs: The Surprising Power of Intradendritic Computation Bartlett W. Mel, Daniel L. Ruderman, Kevin A. Archie
• Orientation Contrast Sensitivity from Long-range Interactions in Visual Cortex Klaus Pawelzik, Udo Ernst, Fred Wolf, Theo Geisel
• Statistically Efficient Estimations Using Cortical Lateral Connections Alexandre Pouget, Kechen Zhang
• An Architectural Mechanism for Direction-tuned Cortical Simple Cells: The Role of Mutual Inhibition Silvio P. Sabatini, Fabio Solari, Giacomo M. Bisio
• Cholinergic Modulation Preserves Spike Timing Under Physiologically Realistic Fluctuating Input Akaysha C. Tang, Andreas M. Bartels, Terrence J. Sejnowski
• A Model of Recurrent Interactions in Primary Visual Cortex Emanuel Todorov, Athanassios Siapas, David Somers
• Neural Learning in Structured Parameter Spaces - Natural Riemannian Gradient Shun-ichi Amari
• For Valid Generalization the Size of the Weights is More Important than the Size of the Network Peter L. Bartlett
• Dynamics of Training Siegfried Bös, Manfred Opper
• Multilayer Neural Networks: One or Two Hidden Layers? Graham Brightwell, Claire Kenyon, Hélène Paugam-Moisy
• Support Vector Regression Machines Harris Drucker, Christopher J. C. Burges, Linda Kaufman, Alex J. Smola, Vladimir Vapnik
• Size of Multilayer Networks for Exact Learning: Analytic Approach André Elisseeff, Hélène Paugam-Moisy
• The Effect of Correlated Input Data on the Dynamics of Learning Søren Halkjær, Ole Winther
• Practical Confidence and Prediction Intervals Tom Heskes
• Statistical Mechanics of the Mixture of Experts Kukjin Kang, Jong-Hoon Oh
• MLP Can Provably Generalize Much Better than VC-bounds Indicate Adam Kowalczyk, Herman L. Ferrá
• Radial Basis Function Networks and Complexity Regularization in Function Learning Adam Krzyzak, Tamás Linder
• An Apobayesian Relative of Winnow Nick Littlestone, Chris Mesterharm
• Noisy Spiking Neurons with Temporal Coding have more Computational Power than Sigmoidal Neurons Wolfgang Maass
• On the Effect of Analog Noise in Discrete-Time Analog Computations Wolfgang Maass, Pekka Orponen
• A Mean Field Algorithm for Bayes Learning in Large Feed-forward Neural Networks Manfred Opper, Ole Winther
• Removing Noise in On-Line Search using Adaptive Batch Sizes Genevieve B. Orr
• Are Hopfield Networks Faster than Conventional Computers? Ian Parberry, Hung-Li Tseng
• Hebb Learning of Features based on their Information Content Ferdinand Peper, Hideki Noda
• The Generalisation Cost of RAMnets Richard Rohwer, Michal Morciniec
• Learning with Noise and Regularizers in Multilayer Neural Networks David Saad, Sara A. Solla
• A Variational Principle for Model-based Morphing Lawrence K. Saul, Michael I. Jordan
• Online Learning from Finite Training Sets: An Analytical Case Study Peter Sollich, David Barber
• Support Vector Method for Function Approximation, Regression Estimation and Signal Processing Vladimir Vapnik, Steven E. Golowich, Alex J. Smola
• The Learning Dynamcis of a Universal Approximator Ansgar H. L. West, David Saad, Ian T. Nabney
• Computing with Infinite Networks Christopher K. I. Williams
• Microscopic Equations in Rough Energy Landscape for Neural Networks K. Y. Michael Wong
• Time Series Prediction using Mixtures of Experts Assaf J. Zeevi, Ron Meir, Robert J. Adler
• Genetic Algorithms and Explicit Search Statistics Shumeet Baluja
• Consistent Classification, Firm and Soft Yoram Baram
• Bayesian Model Comparison by Monte Carlo Chaining David Barber, Christopher M. Bishop
• Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo David Barber, Christopher K. I. Williams
• Regression with Input-Dependent Noise: A Bayesian Treatment Christopher M. Bishop, Cazhaow S. Quazaz
• GTM: A Principled Alternative to the Self-Organizing Map Christopher M. Bishop, Markus Svensén, Christopher K. I. Williams
• The CONDENSATION Algorithm - Conditional Density Propagation and Applications to Visual Tracking Andrew Blake, Michael Isard
• Clustering via Concave Minimization Paul S. Bradley, Olvi L. Mangasarian, W. Nick Street
• Improving the Accuracy and Speed of Support Vector Machines Christopher J. C. Burges, Bernhard Schölkopf
• Estimating Equivalent Kernels for Neural Networks: A Data Perturbation Approach A. Neil Burgess
• Promoting Poor Features to Supervisors: Some Inputs Work Better as Outputs Rich Caruana, Virginia R. de Sa
• Self-Organizing and Adaptive Algorithms for Generalized Eigen-Decomposition Chanchal Chatterjee, Vwani P. Roychowdhury
• Representation and Induction of Finite State Machines using Time-Delay Neural Networks Daniel S. Clouse, C. Lee Giles, Bill G. Horne, Garrison W. Cottrell
• 488 Solutions to the XOR Problem Frans Coetzee, Virginia L. Stonick
• Minimizing Statistical Bias with Queries David A. Cohn
• MIMIC: Finding Optima by Estimating Probability Densities Jeremy S. De Bonet, Charles Lee Isbell Jr., Paul A. Viola
• On a Modification to the Mean Field EM Algorithm in Factorial Learning A. P. Dunmur, D. M. Titterington
• Softening Discrete Relaxation Andrew M. Finch, Richard C. Wilson, Edwin R. Hancock
• Limitations of Self-organizing Maps for Vector Quantization and Multidimensional Scaling Arthur Flexer
• Continuous Sigmoidal Belief Networks Trained using Slice Sampling Brendan J. Frey
• Adaptively Growing Hierarchical Mixtures of Experts Jürgen Fritsch, Michael Finke, Alex Waibel
• Balancing Between Bagging and Bumping Tom Heskes
• LSTM can Solve Hard Long Time Lag Problems Sepp Hochreiter, Juergen Schmidhuber
• One-unit Learning Rules for Independent Component Analysis Aapo Hyvärinen, Erkki Oja
• Recursive Algorithms for Approximating Probabilities in Graphical Models Tommi Jaakkola, Michael I. Jordan
• Combinations of Weak Classifiers Chuanyi Ji, Sheng Ma
• Hidden Markov Decision Trees Michael I. Jordan, Zoubin Ghahramani, Lawrence K. Saul
• Unification of Information Maximization and Minimization Ryotaro Kamimura
• Unsupervised Learning by Convex and Conic Coding Daniel D. Lee, H. Sebastian Seung
• ARC-LH: A New Adaptive Resampling Algorithm for Improving ANN Classifiers Friedrich Leisch, Kurt Hornik
• Bayesian Unsupervised Learning of Higher Order Structure Michael S. Lewicki, Terrence J. Sejnowski
• Source Separation and Density Estimation by Faithful Equivariant SOM Juan K. Lin, Jack D. Cowan, David G. Grier
• NeuroScale: Novel Topographic Feature Extraction using RBF Networks David Lowe, Michael E. Tipping
• Ordered Classes and Incomplete Examples in Classification Mark Mathieson
• Triangulation by Continuous Embedding Marina Meila, Michael I. Jordan
• Combining Neural Network Regression Estimates with Regularized Linear Weights Christopher J. Merz, Michael J. Pazzani
• A Mixture of Experts Classifier with Learning Based on Both Labelled and Unlabelled Data David J. Miller, Hasan S. Uyar
• Learning Bayesian Belief Networks with Neural Network Estimators Stefano Monti, Gregory F. Cooper
• Smoothing Regularizers for Projective Basis Function Networks John E. Moody, Thorsteinn S. Rögnvaldsson
• Competition Among Networks Improves Committee Performance Paul W. Munro, Bambang Parmanto
• Adaptive On-line Learning in Changing Environments Noboru Murata, Klaus-Robert Müller, Andreas Ziehe, Shun-ichi Amari
• Using Curvature Information for Fast Stochastic Search Genevieve B. Orr, Todd K. Leen
• Maximum Likelihood Blind Source Separation: A Context-Sensitive Generalization of ICA Barak A. Pearlmutter, Lucas C. Parra
• A Convergence Proof for the Softassign Quadratic Assignment Algorithm Anand Rangarajan, Alan L. Yuille, Steven Gold, Eric Mjolsness
• Second-order Learning Algorithm with Squared Penalty Term Kazumi Saito, Ryohei Nakano
• Monotonicity Hints Joseph Sill, Yaser S. Abu-Mostafa
• Training Algorithms for Hidden Markov Models using Entropy Based Distance Functions Yoram Singer, Manfred K. Warmuth
• Clustering Sequences with Hidden Markov Models Padhraic Smyth
• Fast Network Pruning and Feature Extraction by using the Unit-OBS Algorithm Achim Stahlberger, Martin Riedmiller
• Separating Style and Content Joshua B. Tenenbaum, William T. Freeman
• Early Brain Damage Volker Tresp, Ralph Neuneier, Hans-Georg Zimmermann
• Probabilistic Interpretation of Population Codes Richard S. Zemel, Peter Dayan, Alexandre Pouget
• VLSI Implementation of Cortical Visual Motion Detection Using an Analog Neural Computer Ralph Etienne-Cummings, Jan Van der Spiegel, Naomi Takahashi, Alyssa Apsel, Paul Mueller
• A Spike Based Learning Neuron in Analog VLSI Philipp Häfliger, Misha Mahowald, Lloyd Watts
• An Analog Implementation of the Constant Average Statistics Constraint For Sensor Calibration John G. Harris, Yu-Ming Chiang
• Analog VLSI Circuits for Attention-Based, Visual Tracking Timothy K. Horiuchi, Tonia G. Morris, Christof Koch, Stephen P. DeWeerth
• Dynamically Adaptable CMOS Winner-Take-All Neural Network Kunihiko Iizuka, Masayuki Miyamoto, Hirofumi Matsui
• An Adaptive WTA using Floating Gate Technology W. Fritz Kruger, Paul E. Hasler, Bradley A. Minch, Christof Koch
• A Micropower Analog VLSI HMM State Decoder for Wordspotting John Lazzaro, John Wawrzynek, Richard P. Lippmann
• Bangs, Clicks, Snaps, Thuds and Whacks: An Architecture for Acoustic Transient Processing Fernando J. Pineda, Gert Cauwenberghs, R. Timothy Edwards
• A Silicon Model of Amplitude Modulation Detection in the Auditory Brainstem André van Schaik, Eric Fragnière, Eric A. Vittoz
• Dynamic Features for Visual Speechreading: A Systematic Comparison Michael S. Gray, Javier R. Movellan, Terrence J. Sejnowski
• Blind Separation of Delayed and Convolved Sources Te-Won Lee, Anthony J. Bell, Russell H. Lambert
• A Constructive RBF Network for Writer Adaptation John C. Platt, Nada Matic
• A New Approach to Hybrid HMM/ANN Speech Recognition using Mutual Information Neural Networks Gerhard Rigoll, Christoph Neukirchen
• Neural Network Modeling of Speech and Music Signals Alex Röbel
• A Constructive Learning Algorithm for Discriminant Tangent Models Diego Sona, Alessandro Sperduti, Antonina Starita
• Dual Kalman Filtering Methods for Nonlinear Prediction, Smoothing and Estimation Eric A. Wan, Alex T. Nelson
• Ensemble Methods for Phoneme Classification Steve R. Waterhouse, Gary Cook
• Effective Training of a Neural Network Character Classifier for Word Recognition Larry S. Yaeger, Richard F. Lyon, Brandyn J. Webb
• Viewpoint Invariant Face Recognition using Independent Component Analysis and Attractor Networks Marian Stewart Bartlett, Terrence J. Sejnowski
• Learning Temporally Persistent Hierarchical Representations Suzanna Becker
• Edges are the 'Independent Components' of Natural Scenes. Anthony J. Bell, Terrence J. Sejnowski
• Compositionality, MDL Priors, and Object Recognition Elie Bienenstock, Stuart Geman, Daniel Potter
• Learning Appearance Based Models: Mixtures of Second Moment Experts Christoph Bregler, Jitendra Malik
• Spatial Decorrelation in Orientation Tuned Cortical Cells Alexander Dimitrov, Jack D. Cowan
• Spatiotemporal Coupling and Scaling of Natural Images and Human Visual Sensitivities Dawei W. Dong
• Selective Integration: A Model for Disparity Estimation Michael S. Gray, Alexandre Pouget, Richard S. Zemel, Steven J. Nowlan, Terrence J. Sejnowski
• ARTEX: A Self-organizing Architecture for Classifying Image Regions Stephen Grossberg, James R. Williamson
• Contour Organisation with the EM Algorithm José A. F. Leite, Edwin R. Hancock
• Visual Cortex Circuitry and Orientation Tuning Trevor Mundel, Alexander Dimitrov, Jack D. Cowan
• Representing Face Images for Emotion Classification Curtis Padgett, Garrison W. Cottrell
• Rapid Visual Processing using Spike Asynchrony Simon J. Thorpe, Jacques Gautrais
• Interpreting Images by Propagating Bayesian Beliefs Yair Weiss
• Salient Contour Extraction by Temporal Binding in a Cortically-based Network Shih-Cheng Yen, Leif H. Finkel
• An Orientation Selective Neural Network for Pattern Identification in Particle Detectors Halina Abramowicz, David Horn, Ury Naftaly, Carmit Sahar-Pikielny
• Adaptive Access Control Applied to Ethernet Data Timothy X. Brown
• Predicting Lifetimes in Dynamically Allocated Memory David A. Cohn, Satinder P. Singh
• Multi-Task Learning for Stock Selection Joumana Ghosn, Yoshua Bengio
• The Neurothermostat: Predictive Optimal Control of Residential Heating Systems Michael C. Mozer, Lucky Vidmar, Robert H. Dodier
• Sequential Tracking in Pricing Financial Options using Model Based and Neural Network Approaches Mahesan Niranjan
• A Comparison between Neural Networks and other Statistical Techniques for Modeling the Relationship between Tobacco and Alcohol and Cancer Tony Plate, Pierre Band, Joel Bert, John Grace
• Reinforcement Learning for Dynamic Channel Allocation in Cellular Telephone Systems Satinder P. Singh, Dimitri P. Bertsekas
• Spectroscopic Detection of Cervical Pre-Cancer through Radial Basis Function Networks Kagan Tumer, Nirmala Ramanujam, Rebecca R. Richards-Kortum, Joydeep Ghosh
• Interpolating Earth-science Data using RBF Networks and Mixtures of Experts Ernest Wan, Don Bone
• Multi-effect Decompositions for Financial Data Modeling Lizhong Wu, John E. Moody
• Multidimensional Triangulation and Interpolation for Reinforcement Learning Scott Davies
• Efficient Nonlinear Control with Actor-Tutor Architecture Kenji Doya
• Local Bandit Approximation for Optimal Learning Problems Michael O. Duff, Andrew G. Barto
• Reinforcement Learning for Mixed Open-loop and Closed-loop Control Eric A. Hansen, Andrew G. Barto, Shlomo Zilberstein
• Multi-Grid Methods for Reinforcement Learning in Controlled Diffusion Processes Stephan Pareigis
• Learning from Demonstration Stefan Schaal
• Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning Jeff G. Schneider
• Analytical Mean Squared Error Curves in Temporal Difference Learning Satinder P. Singh, Peter Dayan
• Learning Decision Theoretic Utilities through Reinforcement Learning Magnus Stensmo, Terrence J. Sejnowski
• On-line Policy Improvement using Monte-Carlo Search Gerald Tesauro, Gregory R. Galperin
• Analysis of Temporal-Diffference Learning with Function Approximation John N. Tsitsiklis, Benjamin Van Roy
• Approximate Solutions to Optimal Stopping Problems John N. Tsitsiklis, Benjamin Van Roy